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Speaker 1: Strap on your parachute. It's time for What Goes Up. Hello,

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Speaker 1: and welcome to What Goes Up, a Bloomberg Weekly Markets podcast.

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Speaker 1: I'm Mike Reagan, and this week on the show, we'll

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Speaker 1: talk to one of the pioneers of factory investing about

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Speaker 1: his new endeavor and why he's taking a more active

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Speaker 1: approach these days, using quantitative methods to hunt for innovative

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Speaker 1: small cap companies to go both long and short on.

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Speaker 1: But first, I think regular listeners are probably wondering now

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Speaker 1: who this week's mystery co host is, So Charlie Pellett

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Speaker 1: taken away and tell them who this week's co host is.

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Speaker 1: This week's mystery co host is Lisa Abramowitz. Lisa is

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Speaker 1: the co host of Bloomberg Surveillance and a mother of two.

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Speaker 1: And even though she has been friends with Mike Reagan

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Speaker 1: for a decade, she's never laughed at one of his jokes.

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Speaker 1: Not even once. Okay, Mike, that is just not true.

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Speaker 1: Let's just set the record straight. I laugh at every

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Speaker 1: single one of your jokes. You could rely on me

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Speaker 1: in the news room to be your joke laugher, So

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Speaker 1: don't even start with that. You're calling Charlie Pellett a liar, Lisa,

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Speaker 1: I'm calling him misinformed by the best out there. Okay,

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Speaker 1: it's you know, it's it's a dangerous power to have

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Speaker 1: to be able to ask Charlie Pellett to read some

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Speaker 1: insult comedy for you. I I this could get this

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Speaker 1: could get dangerous. But Lisa, for listeners who don't know,

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Speaker 1: Lisa and I go pretty far back, I guess. I

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Speaker 1: don't want to say too far back, but back to

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Speaker 1: the days of Bloomberg gad Fly for sure, where I

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Speaker 1: think we were the original too god flies we were,

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Speaker 1: we were, and now of course Lisa the co host

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Speaker 1: of bloomberg Sperience. I need to confess though, in in

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Speaker 1: the pandemic lockdown era, I don't watch it as much

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Speaker 1: as I should, just because my WiFi. I've got a

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Speaker 1: bunch of kids on WiFi and I don't have a TV.

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Speaker 1: I know, excuses, excuses. Don't tell Tom Keened any of this. Please,

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Speaker 1: you don't have a TV. Your kids ate your television.

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Speaker 1: That's why you can't watch for the survillains. That's cool, great,

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Speaker 1: I'm glad. You know what. Keep telling us that it's

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Speaker 1: the internet, it's the broadband save the kids. Now in

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Speaker 1: my office, the kids are all watching their TikTok's the

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Speaker 1: TVs in the TV room. I can't go in there.

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Speaker 1: I'll have I'll just be too distracted. Well, my point is, Lisa,

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Speaker 1: I want a download of your just quick download of

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Speaker 1: your current thoughts of the market. I think of Lisa A.

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Speaker 1: Brahma Witz as what's the best word market sentiment? We'll

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Speaker 1: say cautious? Is cautious? Fair? Well? I think if you

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Speaker 1: lask my co host, they'll just say perme bear. I

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Speaker 1: would say that it's not so much permea bear as

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Speaker 1: it is trying to see around corners. That's my recent

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Speaker 1: line to try to defend myself against all the people

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Speaker 1: who try to slam me down. But the idea is,

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Speaker 1: what are we missing right? I Mean, there's a sort

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Speaker 1: of idea that we're in this incredible melt up that

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Speaker 1: can't be stopped because of the wall of money, whether

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Speaker 1: it's from monetary stimulus or whether it's from fiscal stimulus.

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Speaker 1: And here we are in a situation that seems too

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Speaker 1: good to be true for some people, because if you

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Speaker 1: buy what's been doing well, you will keep doing well.

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Speaker 1: And so there is a question what are we missing

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Speaker 1: either about the economic recovery or about inflation, or about

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Speaker 1: this idea that yield will remain contained for the longer term.

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Speaker 1: And these are some of the conundrums that I think

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Speaker 1: that I spend every day discussing. That is a quick overview.

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Speaker 1: I I love it. You know. I've always been team

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Speaker 1: of Brahma Witz and I gotta say as I've gotten older,

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Speaker 1: I've gotten more quote unquote cautious too. I'd like to

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Speaker 1: say it's you getting older too, but you've been that

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Speaker 1: way since you were much younger, that way, since I

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Speaker 1: was a five year old. Al Right, great, that is

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Speaker 1: the That's the kind of temperature check I needed from Lisa.

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Speaker 1: I'm glad because we haven't talked so long. It's it's

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Speaker 1: it's a shame. But anyway, enough about us. We've got

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Speaker 1: a really fascinating guest this week, and I'm so excited

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Speaker 1: to have him on the show. He uh, it's the

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Speaker 1: founder of a firm called gir Gersteine fisher Um, which

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Speaker 1: he founded at the ripe old age of one just

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Speaker 1: a few years ago. We'll say, we won't say the

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Speaker 1: exact date. He's now gone on to start a new

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Speaker 1: firm called Quent's Capital. His name is Greg Fisher. Greg,

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Speaker 1: welcome to the show. Thank you so much. It's uh,

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Speaker 1: it's really nice to be here with you, Mike and Lisa.

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Speaker 1: And I was I was kind of prepared for this

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Speaker 1: very serious interaction, and I'm having so much fun just

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Speaker 1: watching the two of you interact with one another. I

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Speaker 1: think I'm now officially on team Abrama. It's two alright, alright,

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Speaker 1: there's always there's always room for another on on team.

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Speaker 1: It's a small ship. But Greg, I, I really I'm

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Speaker 1: fascinated by the the approach you're taking at quent Capital Um.

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Speaker 1: And let me describe it briefly the way I understand it.

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Speaker 1: Correct me if I'm wrong, which is highly likely me

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Speaker 1: talking about quantz. It's kind of like a Norwegian guy

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Speaker 1: explaining baseball, so to feel, you know, feel free to

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Speaker 1: correct any of this. But what I think of sort

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Speaker 1: of the methods of a quant um I think of

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Speaker 1: sort of big data, you know, crunching through massive amounts

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Speaker 1: of data trying to find I don't know, momentum or

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Speaker 1: the factors of certain companies that historically have have outperformed.

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Speaker 1: But your approach now applies sort of the quant method

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Speaker 1: to finding finding innovative companies and what I think of

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Speaker 1: investing in innovators. Um, I think that's something sort of

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Speaker 1: completely different, you know, not a lot of historical data

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Speaker 1: to work with, sort of having to take some intuitive

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Speaker 1: leaps about what trends are gonna be like in the future.

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Speaker 1: You know, I'm basing a lot of this on kind

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Speaker 1: of the public face of the quote unquote innovator investment

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Speaker 1: space these days, which is obviously our investment in Cathy.

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Speaker 1: Would you know you can listen to Kathy talk about

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Speaker 1: her strategy for a long time and not hear any ratios,

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Speaker 1: not here, any numbers. So I'm just curious from your perspective,

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Speaker 1: how do you sort of tie the two approaches together.

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Speaker 1: That's a good question, and thanks so well. First, you know,

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Speaker 1: Quent Capital my new firm. I started my original firm

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Speaker 1: back and back then there was like one index fund

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Speaker 1: that nobody used. There were no E T f s,

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Speaker 1: no text messaging, no email, you know, barely an internet,

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Speaker 1: and uh the idea. I was twenty one. I sold

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Speaker 1: the drum set my father bought me for nine bucks,

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Speaker 1: bought a computer, hung up a shingle, opened up a phone,

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Speaker 1: book and started calling people asking if they would allow

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Speaker 1: me to manage their assets using this sort of like

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Speaker 1: data driven investment strategy. It was sort of a funny thing.

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Speaker 1: It kind of worked out and uh and and I

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Speaker 1: was successful for my investors and myself too. I mean

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Speaker 1: it was it was a great good time. I'm now fifty.

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Speaker 1: When I was forty six, I sold the company a

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Speaker 1: few years ago, take a little break, work on this

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Speaker 1: new thing. And I think, like the motivation when I

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Speaker 1: think about quantitative investing, I think people's minds would immediately

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Speaker 1: go to, you know, algorithms and complexities and high frequency

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Speaker 1: trading and all these jazz. But I think about it

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Speaker 1: more as evidence based investing, where you have an idea

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Speaker 1: and you can go back looking at data to sort

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Speaker 1: of prove out that idea that at least you can

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Speaker 1: show that this has worked in the past with a

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Speaker 1: large sample of data, so that it's not completely judgment

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Speaker 1: around your predictions of what will happen in the future.

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Speaker 1: We never know what will happen in the future, but

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Speaker 1: using evidence based investing is how I think about quantitative investing.

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Speaker 1: And if you don't have evidence around what you're doing,

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Speaker 1: if there are things you're doing that you don't have

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Speaker 1: evidence of You can't go back and look at them,

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Speaker 1: there isn't data to try them well. Then, in fact,

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Speaker 1: it's a little bit more of what I think people

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Speaker 1: think of as more traditional active management, where you know

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Speaker 1: it's your gut or your intuition or some prediction into

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Speaker 1: the future. I came up with this term quent Capital,

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Speaker 1: as our firm name blends together the word quant and entrepreneur.

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Speaker 1: In my career, I've been managing portfolios of growth stocks,

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Speaker 1: largely globally, and what I found was that when you're

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Speaker 1: trying to invest in growth stocks, it's very difficult to

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Speaker 1: put a number in the numerator and a number in

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Speaker 1: the denominator and compare things to one another. There's a

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Speaker 1: lot more ambiguity of the valuation of these businesses, particularly

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Speaker 1: in the last ten years. So I use this term

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Speaker 1: quent to show that you know, data can only take

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Speaker 1: you so far um with these small, innovative, disruptive, entrepreneurial

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Speaker 1: style businesses. You know you mentioned TikTok earlier. My kids

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Speaker 1: are watching TikTok, and I noticed you didn't say Facebook.

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Speaker 1: You sort of need to be like I think genuinely

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Speaker 1: resident to the universe you're thinking about, um to really

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Speaker 1: understand it. And I do think that being an entrepreneur myself,

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Speaker 1: my whole life, does make me a better investor in

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Speaker 1: these entrepreneurial activities. Before we get into the idea of

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Speaker 1: entrepreneurship at this moment, I want to talk about the

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Speaker 1: nexus between high frequency trading and the quantitative strategies that

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Speaker 1: you started up before the Internet was as adopted as

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Speaker 1: it is even ten years ago. Did high frequency trading

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Speaker 1: destroy the notion of quantitative investing as you knew it

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Speaker 1: me launched you from initially? It didn't. I mean, I

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Speaker 1: think that to the extent that a lot of things

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Speaker 1: that happened in the industry made costs lower and liquidity higher.

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Speaker 1: Um I think to some degree that sort of helped

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Speaker 1: me personally in my firm for my investors. As you know,

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Speaker 1: costs continue to drive down. But UM, I guess there's

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Speaker 1: always this argument that if you know, if there's some

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Speaker 1: good idea, like let's just use the oldest one we

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Speaker 1: all know, like value investing a good idea, right. We'll

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Speaker 1: probably get to that later, but anyway, so you know,

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Speaker 1: price to book, it's you know, I could teach my

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Speaker 1: nine year old how to do that, And I guess

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Speaker 1: it took a while for people to realize that that

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Speaker 1: was a powerful signal. And then all of a sudden,

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Speaker 1: one day, everybody knows that this thing works, everybody starts

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Speaker 1: doing it, doing it faster than everyone else does, the

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Speaker 1: benefit of that style of investing go away. And I

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Speaker 1: guess there's arguments around all these things. That's an easy

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Speaker 1: one to understand. They're the more complicated ones. I think

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Speaker 1: the issue is just simply, you know, if the reason

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Speaker 1: that this is happening is because of some behavioral factor, um,

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Speaker 1: some flaw in the human system, and or risk, you know,

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Speaker 1: the efficient market stories around these things, if it's one

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Speaker 1: of those two things where you know, I always give

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Speaker 1: an example. Uh, you know, if you're trying to lose weight,

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Speaker 1: and you like me and you like chocolate chip cookies. Um,

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Speaker 1: I come home, there's a chocolate chip cookie on the table.

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Speaker 1: I know if I eat it, I'm gonna gain weight,

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Speaker 1: But I eat it anyway. UM, I just can't help myself.

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Speaker 1: So there are a lot of things that we all

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Speaker 1: know that are well documented that people could do faster

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Speaker 1: than all of us, but they still work. Because they're

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Speaker 1: happening for reasons that are not necessarily about market manipulation

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Speaker 1: or transaction costs or how fast you can trade. Hey, Greg,

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Speaker 1: I want to rewind and and go back to something

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Speaker 1: you said that I find completely fascinating, and that's that

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Speaker 1: you sold a drum set for nine bucks in the nineties.

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Speaker 1: I mean, it's not like a Neil Pert style piece

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Speaker 1: drum set. I I'll tell you why. I I'm a

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Speaker 1: sort of hack musician myself, and I recently bought a

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Speaker 1: drum set off of Facebook marketplace from some high school

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Speaker 1: kid who I think was driving his parents nuts for

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Speaker 1: a hundred and fifty bucks. So there must be deflation

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Speaker 1: and drums going on there this set. Man, I would

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Speaker 1: do anything to have it back. Um. When I sold

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Speaker 1: my company, I there's not much that I really wanted,

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Speaker 1: but I did do one thing. I built a music

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Speaker 1: studio in my basement and bought two drum sets. But uh,

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Speaker 1: and they were more expensive than when I was old.

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Speaker 1: But it was a Slingerland like old school metallic red

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Speaker 1: jazz set. And uh. I played this thing like every

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Speaker 1: minute of my life, starting from when I was twelve

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Speaker 1: years old. I would do anything to have that thing back.

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Speaker 1: I tried actually years ago, but I wasn't successful. But

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Speaker 1: I am still a drummer, and so was my my

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Speaker 1: son actually, but I uh yeah, I think uh, I

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Speaker 1: think music actually and playing the drums was one of

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Speaker 1: the reasons I got into math, just you know, always counting.

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Speaker 1: You know, I hear that a lot from five A

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Speaker 1: lot of smart finance people are are side musicians on

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Speaker 1: the side. It's an interesting phenomenon. But Greg, I wanted

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Speaker 1: to ask you about that notion of the switch from

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Speaker 1: sort of a more index factor based approach to actually

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Speaker 1: more active stock picking. I make a joke that, um,

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Speaker 1: every time we have an active manager on, he goes,

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Speaker 1: you know, this is the year of the stock picker,

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Speaker 1: and as it has been the case, I think in

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Speaker 1: two thousand, two thousand and two that I could go on.

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Speaker 1: But I really do think there's a case now, uh

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Speaker 1: that it seems like it's gonna be true. Active funds

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Speaker 1: majority are once again outperforming their benchmark by a lot

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Speaker 1: of metrics. But I'm curious how you made that lead

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Speaker 1: because here's a guy, or if it really was a

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Speaker 1: big lead, because here's a guy who's spen sort of

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Speaker 1: looking more closely at indexes for decades and then to

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Speaker 1: kind of make that jump into a more active approach.

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Speaker 1: I wonder how is has passive investing, you know, sort

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Speaker 1: of jumped the shark. Has it become a crowded trade

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Speaker 1: in a way. It's a great question. Boy, I can

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Speaker 1: talk for hours about this, so I hope you'll edit this.

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Speaker 1: But but at any rate, so a little a little

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Speaker 1: bit of a background on this. So, um, yeah, I was.

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Speaker 1: If you sort of look me up, you'll see that

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Speaker 1: for the last thirty years, I've been basically telling the

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Speaker 1: world you should build market based portfolios, keep turnover down,

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Speaker 1: keep taxes down, keep an eye on your costs. You know,

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Speaker 1: buy and hold. You know, these things still work. They'll

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Speaker 1: always work. Bill Sharp wrote that paper years back, the

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Speaker 1: Arithmetic of active management. So this idea that there's certain

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Speaker 1: market environments where you know, on the average, we can't

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Speaker 1: be better than average in any market at any moment,

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Speaker 1: at any time, right, he tells, he talks about this,

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Speaker 1: of us will do better, of us will do worse.

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Speaker 1: You add in costs, you knock out another. The math

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Speaker 1: doesn't change. But what I experienced in all the years

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Speaker 1: that I was, you know, sort of working within this

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Speaker 1: market based framework of investing. Um I had. I had

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Speaker 1: actually trademarked the term multi factor in the use of

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Speaker 1: mutual fund investing about twelve so years ago. I launched

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Speaker 1: a bunch of funds. This was like the innovative way

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Speaker 1: to index. It was evidence based investing your building market portfolios.

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Speaker 1: But you have a little more of the things that

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Speaker 1: have worked historically a little less of the things that hadn't.

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Speaker 1: Um So I was doing this stuff for a long time,

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Speaker 1: but what I watched is indexing go from like zero

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Speaker 1: to a lot all of a sudden. I mean, the

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Speaker 1: whole idea of the efficient market idea hypothesis is that

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Speaker 1: if everyone's out there searching for miss price security, spending

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Speaker 1: billions of dollars and lots of energy, and we're all

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Speaker 1: working so hard to find miss price securities, then it's

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Speaker 1: hard to find miss price securities. And you might as

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Speaker 1: well just accept the price of the stocks and markets

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Speaker 1: because on average, everyone is spending a lot of time

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Speaker 1: doing it. Why waste your own time just by it

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Speaker 1: accept everyone else's price. And that's that and and that's

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Speaker 1: a beautiful thing. And it worked quite well for a

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Speaker 1: long time. But I think that when you get to

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Speaker 1: a point like where we are now, where there's been

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Speaker 1: this huge decline in analysts, where the there's this increase

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Speaker 1: in indexing too, depending on who you ask, I think

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Speaker 1: I've heard something like six of all the assets indexed

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Speaker 1: now or something like that. If you have fewer people

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Speaker 1: searching for missed priced securities and no incentive to go

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Speaker 1: out and do it. My son is in school as

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Speaker 1: a finance major. I'm like, don't become an analyst. You

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Speaker 1: know I'm an analyst, but like, there's no money in

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Speaker 1: being an analyst. Um, nobody wants to pay analysts anymore.

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Speaker 1: We just accept market prices. I was kind of kidding,

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Speaker 1: but I wanted to see what his reaction was. Anyway,

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Speaker 1: you get to this point where if everyone is just

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Speaker 1: accepting market prices and fewer people are doing the work

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Speaker 1: to determine if the prices right or wrong, Well, we

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Speaker 1: still have this fifty fifty thing Bill Sharp described, but

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Speaker 1: the distribution around that average would be wider. If you

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Speaker 1: get it right, you'll be more right. If you get

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Speaker 1: it wrong, you'll be more wrong. So I I have

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Speaker 1: this perspective, and I watched this happen, that there is

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Speaker 1: an opportunity. It's still the fifty fifty thing. But if

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Speaker 1: you're the person, if you're on the rights side to that,

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Speaker 1: your ability to outperform by more I believe exists and

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Speaker 1: less two, which is why I actually built a long

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Speaker 1: short strategy versus long only strategy. My last point on this,

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Speaker 1: I published a paper with some co authors last summer

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Speaker 1: was in the Journal of Indexing, and it talked about this.

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Speaker 1: You know, the market environments. You know, we never know

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Speaker 1: when when we're going to enter an environment where the

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Speaker 1: correlation of securities is less positive, where the difference across

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Speaker 1: securities is less positive. We never know when we're going

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Speaker 1: to enter that environment. But what we can know is

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Speaker 1: when we're in those environments, the difference between winners and

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Speaker 1: losers is greater. We've been in an environment for a

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Speaker 1: while where things were just trending together. I had this

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Speaker 1: hypothesis that sooner or later we'll enter an environment where

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Speaker 1: that's not true. Didn't know COVID was going to happen,

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Speaker 1: because as we know, I think last year something like

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Speaker 1: half the securities and the Russell two thousand um had

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Speaker 1: negative returns or something like that. So if you're in

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Speaker 1: an environment where lots of people are indexing, and there's

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Speaker 1: fewer people paying attention to what the price should be.

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Speaker 1: If you're in an environment where the difference between winners

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Speaker 1: and losers is greater. You know, it's my belief that

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Speaker 1: at least for some portion of someone's portfolio, and probably

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Speaker 1: not the majority of it, by the way, but for

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Speaker 1: some portion of someone's portfolio, having a strategy that could

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Speaker 1: take advantage of those themes and trends I think is important.

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Speaker 1: So that's how I got here today. I'd still say

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Speaker 1: that most investors should have like their portfolio in a

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Speaker 1: market based strategy of some capacity. But if there was

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Speaker 1: ever a time to give this thing a shot, I

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Speaker 1: think it's probably now, which is why I'm doing it.

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Speaker 1: I'm hung up on what you said about the right price,

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Speaker 1: and I'm struggling with it, because how do you analyze

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Speaker 1: a stock when it's determined as much by what FED

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Speaker 1: chair J. Powell says today or tomorrow as it does

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Speaker 1: how much they're earning, or how much some people might

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Speaker 1: think they are, or perhaps what somebody on Reddit says

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Speaker 1: about the stock price. In other words, how do you

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Speaker 1: figure out the winners when the right price isn't being

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Speaker 1: determined by fundamentals that are a stagnant concept. That's so

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Speaker 1: so important, Lisa UM. I think Keene said it the

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Speaker 1: best a hundred years ago. It wasn't important what I

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Speaker 1: thought something was worth. It was more important for me

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Speaker 1: to understand what you thought Mike thought, his sister or

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Speaker 1: brother thought it was worth. Like many of us, I've gotten,

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Speaker 1: you know, fascinated with behavioral finance for my whole career.

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Speaker 1: I grew up in the tax business. My family started

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Speaker 1: this tax business and park Slope in the nineteen seventies,

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Speaker 1: and I watched people coming in with like a shoe

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Speaker 1: box filled with their statements from all these different brokerage firms,

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Speaker 1: with all the things they bought, and like the way

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Speaker 1: people were making decisions some Another paper I wrote with

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Speaker 1: another co author mine is titled um Past Performance is

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Speaker 1: Indicative of future beliefs. What we did is we we

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Speaker 1: analyzed and we showed. Look, we know security prices are

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Speaker 1: positively correlated like yesterday, security prices actually have memory. It's

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Speaker 1: not this random walk where today has nothing to do

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Speaker 1: with yesterday. We all make decisions today based on what

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Speaker 1: we ate for breakfast, how we're feeling, what music we

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Speaker 1: listened to whether the sun was shining, whether things went

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Speaker 1: up or down yesterday. So Lisa, you're right read it today,

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Speaker 1: you know, whatever it is like, we have to pay

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Speaker 1: attention to what people think. We can't only look at

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Speaker 1: the fundamentals. But I think the mistake people are making

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Speaker 1: these days is to not look at the fundamentals at all, um.

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Speaker 1: And that's a whole different discussion. This point you make

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Speaker 1: about looking around corners. What you pay for things still matters,

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Speaker 1: it like actually matters, you know. Now the question is

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Speaker 1: what are we valuing. Like in the old days, we

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Speaker 1: used to think sewing machines and buildings were worth something,

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Speaker 1: And these days our greatest assets are the people who

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Speaker 1: work for us, our brand, um, you know, our customer

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Speaker 1: service scores. You know, there's a lot of things that

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Speaker 1: are really hard to measure. We're all trying, but what

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Speaker 1: you pay for things still matters. But this behavioral thing

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Speaker 1: you touched on is critical. You know, Lisa, my fourteen

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Speaker 1: and year old and I we have this game where

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Speaker 1: we try to scare each other, you know, you hide

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Speaker 1: and jump out and and so I'm looking around corners

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Speaker 1: a lot these days as well. I'm a very abrama

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Speaker 1: with approach. But Greg, one thing I love when I

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Speaker 1: talked to uh small cap fund managers is you guys

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Speaker 1: have your heads wrapped around companies a lot of times

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Speaker 1: that I've never even heard of. Um, So if you

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Speaker 1: could just kind of rapid fire through for us some

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Speaker 1: of the stocks that have you excited, uh, sort of

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Speaker 1: on the long end the short end. I mean one

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Speaker 1: in particular, there's this company that we've invested in called

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Speaker 1: smart Eye. I would say, like, there'sn't any one company

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Speaker 1: I would necessarily hone in on in this conversation, but

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Speaker 1: just to use them as an example, it's it's a

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Speaker 1: company in Sweden that basically has created technology that looks

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Speaker 1: at your eyeballs while you're driving in your car and

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Speaker 1: it helps to in advance determine if you're falling asleep

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Speaker 1: or you might get in an accident. So like most

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Speaker 1: a lot of the cars you buy today will have

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Speaker 1: this technology in it. And uh, it's pretty fascinating, small

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Speaker 1: little company, most people have never heard of it. It's

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Speaker 1: done quite well. It's volatile. They should they should apply

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Speaker 1: that to traders too, you know, yeah, and that's right, Um,

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Speaker 1: they probably do these days. Maybe just another one that

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Speaker 1: I think most people probably would have heard of by now.

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Speaker 1: A couple of years ago, they would not have was

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Speaker 1: a fiver. It's become a big company pretty quickly. But

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Speaker 1: I find this shocking. I remember I was at a

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Speaker 1: course at Harvard and there was someone teaching what he

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Speaker 1: called at the time, the Future of Work, and I'm like,

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Speaker 1: the future of work? What the heck is that? Now?

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Speaker 1: This was like five years ago, you know, and like,

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Speaker 1: now we all know what the future of work is.

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Speaker 1: We're in the future. But anyway, but back then, you know,

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Speaker 1: it was, you know, a couple of people from you know,

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Speaker 1: in a basement in Israel somewhere came up with this

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Speaker 1: idea of being able to offer consulting services online for

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Speaker 1: a very small fee relative to hiring like big consulting firms.

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Speaker 1: Now I really could relate to this. When I was

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Speaker 1: building my company, I spent millions of dollars on my brand.

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Speaker 1: I had this logo which I loved. I don't own

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Speaker 1: it anymore, but it was a hummingbird. And uh but

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Speaker 1: I remember, you know, paying a lot of money to

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Speaker 1: come up with this idea, and you know, months and

428
00:22:40,200 --> 00:22:43,520
Speaker 1: strategic analysis and brand strategy and stuff that I totally

429
00:22:43,600 --> 00:22:46,480
Speaker 1: value that is really important these days. But now you know,

430
00:22:46,520 --> 00:22:48,320
Speaker 1: if you want to do that stuff, you go on fiber,

431
00:22:48,400 --> 00:22:50,720
Speaker 1: you type in what you're looking for, and within minutes

432
00:22:50,760 --> 00:22:54,280
Speaker 1: you'll get you know, retired McKinsey executives, PhD s from

433
00:22:54,320 --> 00:22:57,040
Speaker 1: great schools and everybody else you could imagine bidding on

434
00:22:57,080 --> 00:23:00,000
Speaker 1: this project and for like a thousand bucks instead of

435
00:23:00,000 --> 00:23:03,400
Speaker 1: a hundred thousand bucks, you'll get some pretty good work. Um,

436
00:23:03,440 --> 00:23:06,560
Speaker 1: And you can do that for virtually anything these days.

437
00:23:06,640 --> 00:23:10,000
Speaker 1: And that company just you know, coming out of nowhere

438
00:23:10,400 --> 00:23:14,200
Speaker 1: and now taking market share away from huge consulting firms,

439
00:23:14,720 --> 00:23:17,879
Speaker 1: the barriers to entry for these little businesses today to

440
00:23:17,960 --> 00:23:22,240
Speaker 1: get into business. Even in my own business, I remember

441
00:23:22,320 --> 00:23:24,320
Speaker 1: years ago, I bought one of these first voice over

442
00:23:24,440 --> 00:23:27,320
Speaker 1: IP phone systems, Like that was so cool that I

443
00:23:27,359 --> 00:23:31,640
Speaker 1: could have people working for me from home, taking maternity leave,

444
00:23:32,359 --> 00:23:35,359
Speaker 1: working from other states, like it never mattered where they were.

445
00:23:35,760 --> 00:23:38,159
Speaker 1: You call their phone number and they were there. I

446
00:23:38,160 --> 00:23:41,440
Speaker 1: think that was like several hundred thousand dollars of equipment,

447
00:23:41,680 --> 00:23:45,240
Speaker 1: where you know, thousands of dollars a month of consulting contracts.

448
00:23:46,000 --> 00:23:47,960
Speaker 1: Then I start my new business and for like twenty

449
00:23:47,960 --> 00:23:50,560
Speaker 1: dollars per month. Ring Central does all the same stuff

450
00:23:50,600 --> 00:23:52,679
Speaker 1: for me. Um, you know, I could turn it on

451
00:23:52,760 --> 00:23:55,560
Speaker 1: turn it off like it's the most amazing thing. Well,

452
00:23:55,600 --> 00:23:58,080
Speaker 1: the idea here also is how you find some of

453
00:23:58,080 --> 00:23:59,560
Speaker 1: these things. And by the way, as you talk about this,

454
00:23:59,600 --> 00:24:02,000
Speaker 1: I'm thinking out a story today on the Bloomberg about

455
00:24:02,000 --> 00:24:05,840
Speaker 1: how RBC's CEO is worrying about burnout. So his solution,

456
00:24:05,880 --> 00:24:08,480
Speaker 1: in addition to say take some time off, is saying

457
00:24:08,920 --> 00:24:11,320
Speaker 1: you can all download a meditation app on your phone.

458
00:24:11,320 --> 00:24:14,200
Speaker 1: And I was just thinking, really, how successful will that be,

459
00:24:14,280 --> 00:24:17,720
Speaker 1: you know, for forgetting in play satisfaction. They can download

460
00:24:17,760 --> 00:24:20,679
Speaker 1: that meditation app they want going while the kids are

461
00:24:20,680 --> 00:24:23,200
Speaker 1: screaming in the other room. But I'm wondering there's a

462
00:24:23,320 --> 00:24:26,680
Speaker 1: question here about how you find these companies because it's

463
00:24:26,720 --> 00:24:30,520
Speaker 1: not as easy as sort of screening factors or you know,

464
00:24:30,520 --> 00:24:33,080
Speaker 1: the same type of security selection, because where even are

465
00:24:33,119 --> 00:24:36,040
Speaker 1: those securities traded? How do you screen them out? I mean,

466
00:24:36,280 --> 00:24:40,720
Speaker 1: what is the investigative process that you undergo to find

467
00:24:40,720 --> 00:24:43,880
Speaker 1: a company that has the true entrepreneurship values that you're

468
00:24:43,920 --> 00:24:47,560
Speaker 1: looking Well, I mean I could give a couple of

469
00:24:47,600 --> 00:24:50,240
Speaker 1: examples that are I think things that are sort of

470
00:24:50,280 --> 00:24:53,360
Speaker 1: easy to get your head around. The first and the

471
00:24:53,359 --> 00:24:57,120
Speaker 1: most obvious is is the founder still there? I mean

472
00:24:57,119 --> 00:24:58,800
Speaker 1: that's like a zero in a one. You go on

473
00:24:58,800 --> 00:25:01,480
Speaker 1: your Bloomberg machine and you look up founder yes, no,

474
00:25:01,640 --> 00:25:03,400
Speaker 1: and maybe do a little more than that, but that's

475
00:25:03,440 --> 00:25:07,280
Speaker 1: pretty much. So the question is there evidence and there

476
00:25:07,359 --> 00:25:11,439
Speaker 1: is that companies that have their founders still there and

477
00:25:11,520 --> 00:25:15,720
Speaker 1: engaged and and by the way, engaged and still there

478
00:25:15,720 --> 00:25:18,720
Speaker 1: are two different things. But are there companies whose founders

479
00:25:18,760 --> 00:25:22,520
Speaker 1: are still there? Do they? Is there something special about

480
00:25:22,520 --> 00:25:25,560
Speaker 1: an entrepreneur being at a company to a certain size.

481
00:25:25,800 --> 00:25:27,720
Speaker 1: I mean I was an entrepreneur of a certain company.

482
00:25:27,760 --> 00:25:29,760
Speaker 1: I think I added some value, but I also know

483
00:25:29,800 --> 00:25:31,960
Speaker 1: when I got to like eighty employees, I was in

484
00:25:32,040 --> 00:25:34,200
Speaker 1: over my head. You have to know where there's limits

485
00:25:34,200 --> 00:25:36,639
Speaker 1: to that too. So there's times where it adds value

486
00:25:36,640 --> 00:25:38,760
Speaker 1: in times where it might take away. But I think

487
00:25:38,800 --> 00:25:40,840
Speaker 1: the question is the entrepreneur. The other thing is and

488
00:25:40,960 --> 00:25:43,760
Speaker 1: one of my adviser's great friends, her name's Francis Fry.

489
00:25:43,840 --> 00:25:46,840
Speaker 1: She's a Harvard professor. You know, she always says like

490
00:25:47,840 --> 00:25:52,280
Speaker 1: the best leaders are the ones whose organizations thrive in

491
00:25:52,359 --> 00:25:57,280
Speaker 1: their absence. So when this founder does leave, do they

492
00:25:57,359 --> 00:26:01,520
Speaker 1: leave behind the crumbs that keep the culture of that

493
00:26:01,800 --> 00:26:04,639
Speaker 1: entrepreneur entrepreneurship still running through the company. And how do

494
00:26:04,640 --> 00:26:07,159
Speaker 1: you go looking for those things? What are those things? Well,

495
00:26:07,200 --> 00:26:11,480
Speaker 1: there are things like innovation, right, how do you measure innovation?

496
00:26:11,480 --> 00:26:13,920
Speaker 1: How many H one B VISs file are filed? How

497
00:26:13,920 --> 00:26:17,119
Speaker 1: many patents are filed? Who filed them? Um, there's you

498
00:26:17,119 --> 00:26:19,000
Speaker 1: know how much R and D do they spend? You

499
00:26:19,040 --> 00:26:21,320
Speaker 1: can pull that right off their income statement. Lots of

500
00:26:21,359 --> 00:26:24,040
Speaker 1: things you could do. Now, you're not going to find

501
00:26:24,359 --> 00:26:27,280
Speaker 1: these things unless you know what you're looking for. So

502
00:26:27,520 --> 00:26:30,080
Speaker 1: the information and you know, quant strategies in my mind

503
00:26:30,119 --> 00:26:32,520
Speaker 1: has always been you know, we all have access to

504
00:26:32,520 --> 00:26:34,440
Speaker 1: the same data, but it's all about what questions are

505
00:26:34,440 --> 00:26:37,280
Speaker 1: you asking? What are the intuitions? Um? So, I would

506
00:26:37,320 --> 00:26:39,720
Speaker 1: just say things like that are examples of how you

507
00:26:39,760 --> 00:26:42,960
Speaker 1: might go finding these companies globally. And there are a

508
00:26:42,960 --> 00:26:45,440
Speaker 1: lot of them, and there are many of them that

509
00:26:45,520 --> 00:26:48,280
Speaker 1: there are very few analysts following because you know, when

510
00:26:48,280 --> 00:26:51,200
Speaker 1: you're looking at smaller companies. You know mentioned earlier that

511
00:26:51,359 --> 00:26:53,800
Speaker 1: you know the whole of indexing concept, but in the

512
00:26:54,000 --> 00:26:59,200
Speaker 1: smaller company stocks there are even fewer people following them. Frequently. Greg,

513
00:26:59,240 --> 00:27:02,240
Speaker 1: I've got to see great trick that will get Lisa

514
00:27:02,560 --> 00:27:06,280
Speaker 1: really excited. You're ready watch her. We're on zoom. The

515
00:27:06,520 --> 00:27:09,280
Speaker 1: listeners can't see your facial expression, but if you watch,

516
00:27:09,640 --> 00:27:12,119
Speaker 1: you'll see you'll see a reaction, and that is to

517
00:27:12,240 --> 00:27:16,159
Speaker 1: switch gears and talk about the macro outlook and the

518
00:27:16,320 --> 00:27:19,800
Speaker 1: rising yields and everything like that. You can see Lisa's

519
00:27:19,840 --> 00:27:22,840
Speaker 1: She's getting excited already. But and the reason I want

520
00:27:22,840 --> 00:27:23,960
Speaker 1: to ask you is because a lot of you know,

521
00:27:24,000 --> 00:27:27,600
Speaker 1: a lot of uh equity managers that I talked will

522
00:27:27,640 --> 00:27:29,879
Speaker 1: be like, well, sir, I'm not a macro guy. I

523
00:27:29,880 --> 00:27:32,120
Speaker 1: don't give it much thought, but I know you are,

524
00:27:32,280 --> 00:27:34,840
Speaker 1: and I'm curious just you know, a what kind of

525
00:27:34,880 --> 00:27:39,880
Speaker 1: your your take on the current macro environment is inflation? Uh,

526
00:27:39,960 --> 00:27:43,280
Speaker 1: you know, the rotation from cyclical to growth and back

527
00:27:43,320 --> 00:27:45,600
Speaker 1: and forth every day. It's a different, you know, side

528
00:27:45,600 --> 00:27:48,679
Speaker 1: of the boat. And also kind of how important it

529
00:27:48,760 --> 00:27:51,119
Speaker 1: is to your strategy. I want to I want to

530
00:27:51,160 --> 00:27:52,960
Speaker 1: answer the question because I do have an opinion and

531
00:27:53,000 --> 00:27:55,280
Speaker 1: thoughts around it, but just to take a step back,

532
00:27:55,480 --> 00:27:59,399
Speaker 1: I think one important thing about this strategy or any strategy,

533
00:27:59,520 --> 00:28:04,040
Speaker 1: that the idea around small cap stocks um. So probably

534
00:28:04,200 --> 00:28:07,280
Speaker 1: anyone listening to this has seen this data. If you

535
00:28:07,359 --> 00:28:09,800
Speaker 1: go back a hundred years and you look at all

536
00:28:09,800 --> 00:28:12,840
Speaker 1: the data we have in every country, and you do

537
00:28:12,920 --> 00:28:15,520
Speaker 1: like rolling periods, you know, like rolling ten year periods

538
00:28:15,560 --> 00:28:17,880
Speaker 1: or the whole hundred years, or however you look at it,

539
00:28:18,359 --> 00:28:21,680
Speaker 1: the fact is that small company stocks have earned about

540
00:28:21,720 --> 00:28:25,600
Speaker 1: two percentage points per year more than large companies over

541
00:28:25,640 --> 00:28:29,640
Speaker 1: the long term and over most five, ten, fifteen year periods.

542
00:28:30,440 --> 00:28:33,479
Speaker 1: Turns out, however, in the last ten years, the reverse

543
00:28:33,520 --> 00:28:35,840
Speaker 1: has been true. We saw this change a little bit

544
00:28:35,880 --> 00:28:38,760
Speaker 1: in the last few months, but the reverse has been

545
00:28:38,760 --> 00:28:43,600
Speaker 1: true that actually large companies have outperformed small companies by

546
00:28:43,600 --> 00:28:45,640
Speaker 1: almost the same amount two percent a year for the

547
00:28:45,680 --> 00:28:49,720
Speaker 1: prior decade. Is that is that the Bogel effect to

548
00:28:49,800 --> 00:28:51,640
Speaker 1: some degree, the effect, you know, I don't know what

549
00:28:51,760 --> 00:28:53,760
Speaker 1: to blame it on. There are people who have blame

550
00:28:53,800 --> 00:28:57,200
Speaker 1: it on macro issues, like the banks cut off small

551
00:28:57,240 --> 00:29:00,560
Speaker 1: companies and stopped lending to them after the financial isis,

552
00:29:00,720 --> 00:29:05,000
Speaker 1: or you know, the indexing concepts of big getting bigger

553
00:29:05,040 --> 00:29:06,960
Speaker 1: because we're all just buying what we love and the

554
00:29:06,960 --> 00:29:09,680
Speaker 1: most popular things get the highest prices, and the indexes

555
00:29:09,720 --> 00:29:11,560
Speaker 1: are generally cap weighted. And I don't know, there's a

556
00:29:11,560 --> 00:29:13,040
Speaker 1: lot of answers to this. I don't think any of

557
00:29:13,160 --> 00:29:16,200
Speaker 1: us ever really know the answer as to why things happened.

558
00:29:17,040 --> 00:29:18,880
Speaker 1: But I think the one thing I would come back

559
00:29:18,920 --> 00:29:23,360
Speaker 1: to is the idea that little, risky businesses earning a

560
00:29:23,600 --> 00:29:28,760
Speaker 1: lower rate of return on the average than large, established

561
00:29:28,840 --> 00:29:32,280
Speaker 1: institutional players. It's it's hard to get my head around

562
00:29:32,320 --> 00:29:35,640
Speaker 1: that like this risk return thing should bear fruit over

563
00:29:35,680 --> 00:29:52,240
Speaker 1: a long period. Before you go Macro, I actually want

564
00:29:52,240 --> 00:29:54,480
Speaker 1: to push back a little bike because one of the

565
00:29:54,520 --> 00:29:57,720
Speaker 1: things that I've noticed recently about the Macro outlook, Wait,

566
00:29:57,760 --> 00:29:59,920
Speaker 1: push push back on Greg, not on me, though, right,

567
00:30:00,400 --> 00:30:03,200
Speaker 1: push back on you. I can't handle the Abromo pushback.

568
00:30:03,920 --> 00:30:06,640
Speaker 1: I'm I'm on train Reagan. I just think that, you know,

569
00:30:06,760 --> 00:30:11,040
Speaker 1: recently the Macro calls have gotten, you know, both really

570
00:30:11,040 --> 00:30:14,320
Speaker 1: convergent when it comes to generally positive and really divergent

571
00:30:14,360 --> 00:30:16,920
Speaker 1: when it comes to inflation. The issue, though, that I

572
00:30:16,920 --> 00:30:18,560
Speaker 1: want to pick up on Greg, that I think that

573
00:30:18,600 --> 00:30:22,400
Speaker 1: you're talking about that I find fascinating is this idea

574
00:30:22,520 --> 00:30:26,120
Speaker 1: of betting on smaller companies and how that restrains bigger

575
00:30:26,160 --> 00:30:30,280
Speaker 1: investors because you cannot commit that much capital to those

576
00:30:30,320 --> 00:30:33,959
Speaker 1: players efficiently while doing the work that you're talking about,

577
00:30:34,040 --> 00:30:38,920
Speaker 1: how much is the small versus big argument also applicable

578
00:30:39,120 --> 00:30:42,680
Speaker 1: to portfolio managers to this idea that smaller fund managers

579
00:30:42,720 --> 00:30:46,080
Speaker 1: actually will start out performing in a meaningful way in

580
00:30:46,080 --> 00:30:49,400
Speaker 1: this current environment. Oh, that's such a great point, and

581
00:30:49,400 --> 00:30:52,240
Speaker 1: I've obviously one that I love hearing. But yeah, there's

582
00:30:52,320 --> 00:30:55,040
Speaker 1: there is evidence in the data, and it makes sense

583
00:30:55,040 --> 00:30:57,200
Speaker 1: based on what you've said that you know, small fund

584
00:30:57,200 --> 00:30:59,680
Speaker 1: buying small names should do better than a large fund

585
00:30:59,680 --> 00:31:02,200
Speaker 1: buying small names because large cons can't really buy the

586
00:31:02,240 --> 00:31:04,360
Speaker 1: small names and make it have and have it make

587
00:31:04,400 --> 00:31:06,720
Speaker 1: a material impact. Well. And I guess that the way

588
00:31:06,720 --> 00:31:09,560
Speaker 1: that that folds into the macro is where we are

589
00:31:09,600 --> 00:31:12,440
Speaker 1: in the economic cycle. There seems to be a turn

590
00:31:13,040 --> 00:31:16,520
Speaker 1: under the markets. People have priced in very low rates

591
00:31:16,680 --> 00:31:19,800
Speaker 1: that was a main driver of performance people have priced

592
00:31:19,880 --> 00:31:22,440
Speaker 1: in a new economic cycle. I'll be at one that's

593
00:31:22,520 --> 00:31:25,520
Speaker 1: very different given the hangover of debt. Is the only

594
00:31:25,600 --> 00:31:30,440
Speaker 1: way to meaningfully outperformed now really have to do with

595
00:31:30,720 --> 00:31:33,160
Speaker 1: names in a way that it just hasn't because of

596
00:31:33,160 --> 00:31:35,160
Speaker 1: where we are in the rate cycle. If nothing else,

597
00:31:36,240 --> 00:31:39,080
Speaker 1: I do believe that there's some absolute truth to that,

598
00:31:39,160 --> 00:31:41,960
Speaker 1: and that that will be a factor in the performance

599
00:31:42,000 --> 00:31:45,520
Speaker 1: of managers going forward. I do want to also touch

600
00:31:45,560 --> 00:31:48,840
Speaker 1: on coming back, So I would define this this idea

601
00:31:48,920 --> 00:31:51,680
Speaker 1: of investors generally don't have much in the way of

602
00:31:51,680 --> 00:31:54,680
Speaker 1: small companies to begin with, Like they're under allocated, and

603
00:31:54,720 --> 00:31:56,800
Speaker 1: you can see that in the data. Um, Like if

604
00:31:56,840 --> 00:31:58,719
Speaker 1: you just look at the total market index, it's like

605
00:31:58,800 --> 00:32:04,400
Speaker 1: ten eleven small cap and you know, large cap, and

606
00:32:04,440 --> 00:32:06,160
Speaker 1: that's sort of a proxy for all of us on

607
00:32:06,200 --> 00:32:08,880
Speaker 1: the average. Yet consultants tell everyone they should have like

608
00:32:09,520 --> 00:32:13,080
Speaker 1: in small business. Now investors will uh, institutional investors will

609
00:32:13,160 --> 00:32:16,479
Speaker 1: ratchet up small business by private equity verse public equity,

610
00:32:16,480 --> 00:32:18,680
Speaker 1: and I have some thoughts on that too. But at

611
00:32:18,680 --> 00:32:21,240
Speaker 1: the end of the day, small business investing people are

612
00:32:21,240 --> 00:32:25,440
Speaker 1: tend to be uh, sort of under allocated. Combine that

613
00:32:25,480 --> 00:32:27,840
Speaker 1: with they've done poorly for the last ten years by

614
00:32:27,880 --> 00:32:31,160
Speaker 1: a lot, you know, I mean bigger than ever. Um.

615
00:32:31,200 --> 00:32:33,960
Speaker 1: I think there's a good environment for you know, taking

616
00:32:33,960 --> 00:32:36,000
Speaker 1: a close look at what you have as an investor

617
00:32:36,040 --> 00:32:39,080
Speaker 1: in small company stocks, and then combine that with doing

618
00:32:39,120 --> 00:32:42,400
Speaker 1: the work being a small fund being able to outperform

619
00:32:42,480 --> 00:32:45,520
Speaker 1: based on these trends. We see the other thing about

620
00:32:45,560 --> 00:32:48,719
Speaker 1: the macro and interest rates in inflation. Um, they say

621
00:32:48,760 --> 00:32:50,680
Speaker 1: you've mentioned something a couple of times, and it makes

622
00:32:50,680 --> 00:32:53,000
Speaker 1: me think of something. You know, I I think the

623
00:32:53,960 --> 00:32:59,320
Speaker 1: ten year bond peaked at like six back, and the

624
00:32:59,400 --> 00:33:03,680
Speaker 1: long term average is I think six percent. And uh,

625
00:33:03,760 --> 00:33:06,840
Speaker 1: we just went from fifty basis points roughly in August

626
00:33:06,920 --> 00:33:10,800
Speaker 1: to one point seven percent. Now I'm rounding, but that's close, like,

627
00:33:10,920 --> 00:33:14,600
Speaker 1: and that surprised everyone. I don't think people were expecting that. Now.

628
00:33:15,320 --> 00:33:17,320
Speaker 1: It's shocking to me that we're all like worried about

629
00:33:17,320 --> 00:33:22,240
Speaker 1: two when like we've seen sixteen almost and the average

630
00:33:22,280 --> 00:33:25,520
Speaker 1: was six, like getting a three or four. To me,

631
00:33:26,320 --> 00:33:28,440
Speaker 1: I'm not I'm not good at predicting the future, so

632
00:33:28,480 --> 00:33:30,640
Speaker 1: I'm not saying we're gona have massive inflation, but I'm

633
00:33:30,680 --> 00:33:32,080
Speaker 1: just like the idea that we could get to three

634
00:33:32,160 --> 00:33:34,040
Speaker 1: or four, Like, I don't think that should be like

635
00:33:34,080 --> 00:33:37,360
Speaker 1: a big shocker. I think it's possible that can happen.

636
00:33:37,760 --> 00:33:40,400
Speaker 1: And I think this point you made earlier about um,

637
00:33:40,400 --> 00:33:43,120
Speaker 1: you know, as human beings, we all underweight the low

638
00:33:43,200 --> 00:33:45,680
Speaker 1: probability event, and that's the one that we always have

639
00:33:45,720 --> 00:33:48,600
Speaker 1: to worry about. Um, so paying a little bit of attention.

640
00:33:48,640 --> 00:33:51,000
Speaker 1: So if I'm an investor, I'm saying, what percentage of

641
00:33:51,040 --> 00:33:54,600
Speaker 1: my portfolio do I have invested in things that might

642
00:33:54,680 --> 00:33:57,800
Speaker 1: do well if we see that happen at least something,

643
00:33:58,160 --> 00:34:00,360
Speaker 1: you know, like the idea that there's a zero chance

644
00:34:00,440 --> 00:34:03,000
Speaker 1: that could happen is probably a mistake. There is at

645
00:34:03,080 --> 00:34:05,640
Speaker 1: least some chance that that could happen. Now, as it

646
00:34:05,680 --> 00:34:08,279
Speaker 1: relates to you know, investing inequities, I think we've all

647
00:34:08,360 --> 00:34:12,480
Speaker 1: learned that rising discount rates are the enemy to the

648
00:34:12,520 --> 00:34:16,560
Speaker 1: financial asset, you know, and a surprise rise in interest

649
00:34:16,640 --> 00:34:20,160
Speaker 1: rates are like really bad. So if we all just

650
00:34:20,239 --> 00:34:22,200
Speaker 1: expect rates to go up, and we know they're going

651
00:34:22,239 --> 00:34:24,359
Speaker 1: to go up, and we're all anticipating they go up,

652
00:34:24,680 --> 00:34:29,239
Speaker 1: then that's not that horrible. Like companies optimize around what

653
00:34:29,280 --> 00:34:31,359
Speaker 1: they know and just deal with it, and over time

654
00:34:31,360 --> 00:34:33,480
Speaker 1: we're probably okay. But the thing that we're all afraid

655
00:34:33,480 --> 00:34:36,040
Speaker 1: of is a shock of surprise something we weren't expecting.

656
00:34:36,320 --> 00:34:38,239
Speaker 1: Like we woke up tomorrow and the ten year was

657
00:34:38,280 --> 00:34:40,560
Speaker 1: at three percent, I think we'd all be like really scared,

658
00:34:40,840 --> 00:34:43,520
Speaker 1: at least for the short term. Now you look at

659
00:34:43,520 --> 00:34:46,400
Speaker 1: the NASDAC and interest rates over the last two months,

660
00:34:46,520 --> 00:34:49,080
Speaker 1: and you've seen this negative correlation of rates go up

661
00:34:49,200 --> 00:34:52,279
Speaker 1: growth stocks go down. After we all got comfortable at

662
00:34:52,280 --> 00:34:55,120
Speaker 1: the one point seven and the prices sort of got

663
00:34:55,160 --> 00:34:58,480
Speaker 1: baked in. Now it looks like that relationship has broke

664
00:34:58,560 --> 00:35:01,960
Speaker 1: down where it's not happening anymore. So it's a little

665
00:35:02,000 --> 00:35:05,280
Speaker 1: bit about you know this, understanding what everybody's thinking again

666
00:35:05,760 --> 00:35:09,360
Speaker 1: versus what actually happened. Greg. My my goal is a

667
00:35:09,440 --> 00:35:12,720
Speaker 1: journalist is to find someone who bought that long bond

668
00:35:12,760 --> 00:35:15,600
Speaker 1: you're talking about in the eighties and and held soul maturity.

669
00:35:15,640 --> 00:35:20,160
Speaker 1: They whoever they are, is probably the world's biggest investing

670
00:35:20,200 --> 00:35:24,239
Speaker 1: genius out there. But hey, guys, I think that's enough

671
00:35:24,280 --> 00:35:26,520
Speaker 1: of the serious stuff. Okay, It's time for the more

672
00:35:26,560 --> 00:35:30,000
Speaker 1: important stuff, which is our tradition. Here the craziest thing

673
00:35:30,360 --> 00:35:32,960
Speaker 1: we saw in markets this week, Lisa, I know I

674
00:35:33,000 --> 00:35:35,320
Speaker 1: sent you like a thousand emails about this podcast, but

675
00:35:35,360 --> 00:35:37,360
Speaker 1: hopefully you read the one about the crazy things. I

676
00:35:37,400 --> 00:35:40,520
Speaker 1: have a lot of faith in your ability to bring

677
00:35:40,560 --> 00:35:44,080
Speaker 1: some crazy market stories to us this week. Ghost cattle.

678
00:35:45,239 --> 00:35:48,760
Speaker 1: That's I'm just gonna say, ghost cattle. There were cattle,

679
00:35:49,000 --> 00:35:54,520
Speaker 1: two hundred thousand cattle that seemed to disappear from Tyson

680
00:35:55,520 --> 00:36:00,279
Speaker 1: and it turns out it was due to fraudulent future

681
00:36:00,360 --> 00:36:04,000
Speaker 1: trading among other things. Uh, they never existed. There's two

682
00:36:04,200 --> 00:36:07,600
Speaker 1: d cattle and uh. I could go in further to

683
00:36:07,680 --> 00:36:10,160
Speaker 1: this story, but it's um. I will say that ghost

684
00:36:10,239 --> 00:36:12,840
Speaker 1: cattle is the strangest thing that I read about. So

685
00:36:13,719 --> 00:36:18,239
Speaker 1: someone was naked naked sure cattle? Well, it was Easterday

686
00:36:18,320 --> 00:36:22,000
Speaker 1: Ranches submitted. I'm not as intimate with the story, but

687
00:36:22,080 --> 00:36:24,400
Speaker 1: there was there was some issue. There were some issues

688
00:36:24,440 --> 00:36:28,120
Speaker 1: with the tickets around the particular cattle, and then there

689
00:36:28,160 --> 00:36:31,520
Speaker 1: was an insolvency having to do with this particular ranch.

690
00:36:31,600 --> 00:36:35,120
Speaker 1: But the idea of you know, ghost cattle, to me

691
00:36:35,640 --> 00:36:38,600
Speaker 1: is a fantastic market. You know, I knew you would

692
00:36:38,640 --> 00:36:42,480
Speaker 1: not disappoint on this, on this metric, and I you

693
00:36:42,560 --> 00:36:45,879
Speaker 1: came prepared. I that is a strong, first crazy thing.

694
00:36:45,960 --> 00:36:47,520
Speaker 1: That's cool. I don't I don't know that I'm going

695
00:36:47,600 --> 00:36:50,839
Speaker 1: to have anything better than that. Alright, Greg, You're gonna pass.

696
00:36:50,880 --> 00:36:54,040
Speaker 1: You can pass. It's at least it's a tough act

697
00:36:54,080 --> 00:36:57,040
Speaker 1: to follow. I I I have to follow her because

698
00:36:57,080 --> 00:36:59,440
Speaker 1: this is my gimmick. But but let's hear what you

699
00:36:59,480 --> 00:37:03,280
Speaker 1: got well. I guess this is not like new information

700
00:37:03,320 --> 00:37:06,200
Speaker 1: anybody listening, because we're all following this stuff. But I

701
00:37:06,880 --> 00:37:11,480
Speaker 1: do find it shocking. How like we watched this recent

702
00:37:11,680 --> 00:37:16,320
Speaker 1: episode of this you know, dollar Money Manager get accepted

703
00:37:16,360 --> 00:37:19,919
Speaker 1: by all these large institutional players that are just looking

704
00:37:19,960 --> 00:37:22,960
Speaker 1: to make more money somehow, and watch this thing just

705
00:37:23,080 --> 00:37:27,400
Speaker 1: like wither away overnight. And the idea that in this society,

706
00:37:27,440 --> 00:37:29,600
Speaker 1: like you would think we would have learned by now

707
00:37:29,719 --> 00:37:32,359
Speaker 1: from all these experiences over the last twenty years, if

708
00:37:32,400 --> 00:37:35,400
Speaker 1: not even the last hundred, Like, I just find it fastening.

709
00:37:35,480 --> 00:37:37,560
Speaker 1: This keeps happening over and over again, and then the

710
00:37:37,560 --> 00:37:40,759
Speaker 1: other thing connected to that and another firm that's out there,

711
00:37:41,560 --> 00:37:46,200
Speaker 1: this idea that, like religious beliefs um are like driving

712
00:37:46,239 --> 00:37:49,520
Speaker 1: people's risk taking behavior. I mean, with all the science

713
00:37:49,560 --> 00:37:51,480
Speaker 1: we have out there today, I find that kind of

714
00:37:51,560 --> 00:37:53,239
Speaker 1: weird too, you know, like it's just hard for me

715
00:37:53,280 --> 00:37:55,200
Speaker 1: to get my head around that. You know, you know,

716
00:37:55,320 --> 00:37:57,040
Speaker 1: you raise a good point, And that's one of the

717
00:37:57,080 --> 00:37:59,600
Speaker 1: crazy aspects of this story, the Archagas story is what

718
00:37:59,640 --> 00:38:02,759
Speaker 1: you're talking about, twenty billion dollars to zero overnight. It

719
00:38:02,960 --> 00:38:06,200
Speaker 1: is crazy, and yet it is so fundamental to human nature.

720
00:38:06,360 --> 00:38:09,560
Speaker 1: So when somebody presents themselves with confidence and they're dealing

721
00:38:09,560 --> 00:38:11,879
Speaker 1: with a lot of money, everybody trusts them. And when

722
00:38:11,920 --> 00:38:15,120
Speaker 1: greed outweighs fear. You know, this is how you get

723
00:38:15,160 --> 00:38:18,320
Speaker 1: scenarios just like this. Yeah, and that's why I always

724
00:38:18,360 --> 00:38:21,279
Speaker 1: liked the data and the science of investing, Like, you know,

725
00:38:21,320 --> 00:38:23,960
Speaker 1: show me some proof. Yeah, just to talk to the

726
00:38:23,960 --> 00:38:25,880
Speaker 1: house book here a little bit. There's a great story

727
00:38:25,960 --> 00:38:30,480
Speaker 1: in this week's Business Week about the whole Archagoes drama, Lisa,

728
00:38:30,760 --> 00:38:33,520
Speaker 1: Eric Shatzker, your colleague on TV with the bio in there.

729
00:38:34,080 --> 00:38:36,680
Speaker 1: All right, both are excellent things. I I gotta hand

730
00:38:36,719 --> 00:38:37,960
Speaker 1: it to you. I think I'm only going to take

731
00:38:37,960 --> 00:38:40,879
Speaker 1: the bronze this time in the craziest thing, first time

732
00:38:40,880 --> 00:38:44,600
Speaker 1: ever that I haven't haven't meddled higher. But I will

733
00:38:45,000 --> 00:38:47,719
Speaker 1: say mine's not necessarily the craziest, but perhaps the most

734
00:38:47,760 --> 00:38:50,279
Speaker 1: interesting thing. And at least I I thought of you

735
00:38:50,520 --> 00:38:52,839
Speaker 1: when I conjured this up, because I want to hear

736
00:38:52,880 --> 00:38:55,319
Speaker 1: your take on it. And this is courtesy of Matt

737
00:38:55,400 --> 00:38:58,759
Speaker 1: Levine's excellent Money Stuff newsletter. Lisa, have you heard of

738
00:38:58,800 --> 00:39:02,360
Speaker 1: this concept the green um, which is if you're selling

739
00:39:02,400 --> 00:39:05,400
Speaker 1: a green bond, you can price it at a lower

740
00:39:05,600 --> 00:39:08,560
Speaker 1: rate than a regular corporate bond because there's so much

741
00:39:08,800 --> 00:39:12,719
Speaker 1: greg to your point about you know, religion influencing people's

742
00:39:12,840 --> 00:39:15,960
Speaker 1: desire for sustainability and for diversity and for all the

743
00:39:16,120 --> 00:39:19,000
Speaker 1: s D type of stuff is causing so much capital

744
00:39:19,080 --> 00:39:21,280
Speaker 1: to to chase it that you can price a green

745
00:39:21,480 --> 00:39:24,040
Speaker 1: bond at a lower rate than a regular bond. And

746
00:39:24,080 --> 00:39:25,800
Speaker 1: as you know, as I'm kind of a tree hugger

747
00:39:25,840 --> 00:39:28,440
Speaker 1: at heart, so I I'm kind of happy to hear this,

748
00:39:28,480 --> 00:39:30,200
Speaker 1: But as a market guy, I'm like, wait a minute,

749
00:39:30,560 --> 00:39:33,800
Speaker 1: some something weird here. And the one that that Levin

750
00:39:33,840 --> 00:39:37,839
Speaker 1: wrote about is actually a revolver loan that black Rock

751
00:39:38,040 --> 00:39:40,200
Speaker 1: sold to a bunch of banks, and it's a one

752
00:39:40,320 --> 00:39:44,400
Speaker 1: basis point incentive built into the rate depending on whether

753
00:39:44,440 --> 00:39:48,279
Speaker 1: block Rock hits certain sustainability UH and diversity goals at

754
00:39:48,280 --> 00:39:51,400
Speaker 1: one basis point. So all the lawyers and paperwork that

755
00:39:51,480 --> 00:39:54,640
Speaker 1: went into determine this for a one basis point move.

756
00:39:54,680 --> 00:39:56,920
Speaker 1: But I guess the idea is that black Rock can

757
00:39:57,040 --> 00:39:59,399
Speaker 1: can show this to other investors and kind of get

758
00:39:59,400 --> 00:40:01,759
Speaker 1: the ball roll for this type more of this type

759
00:40:01,760 --> 00:40:04,359
Speaker 1: of product out there. Curious what you both think of

760
00:40:04,360 --> 00:40:07,799
Speaker 1: this whole whole notion that's the price of pr I

761
00:40:07,840 --> 00:40:10,399
Speaker 1: think that that's essentially what this is. I mean, let's

762
00:40:10,400 --> 00:40:12,759
Speaker 1: just put it. Let's call it spade a spade. I mean, look,

763
00:40:12,960 --> 00:40:15,919
Speaker 1: I think that there's some very real goals, and I

764
00:40:15,960 --> 00:40:19,080
Speaker 1: would totally agree and applaud goals to try to make

765
00:40:19,200 --> 00:40:22,080
Speaker 1: our world a little bit more sustainable so that we

766
00:40:22,120 --> 00:40:25,680
Speaker 1: can avoid that two percentage point or that two increase

767
00:40:25,719 --> 00:40:27,920
Speaker 1: in temperature, which is sort of the Nopeman no go

768
00:40:28,200 --> 00:40:31,960
Speaker 1: kind of place. I think that whether some of these

769
00:40:32,000 --> 00:40:36,759
Speaker 1: financial incentives achieve that talked about looking around corners, the

770
00:40:36,800 --> 00:40:40,120
Speaker 1: skeptic in me always wonders how much is greenwashing and

771
00:40:40,160 --> 00:40:44,360
Speaker 1: how much is reality? That said, the more emphasis. I

772
00:40:44,400 --> 00:40:46,160
Speaker 1: don't know. I'm not going to get into a political spiel,

773
00:40:46,280 --> 00:40:48,359
Speaker 1: but what I will say is this said, I think that,

774
00:40:48,600 --> 00:40:52,640
Speaker 1: you know, there is an incredible amount of money looking

775
00:40:53,080 --> 00:40:57,480
Speaker 1: to make companies look better and look more responsible. That

776
00:40:57,520 --> 00:40:59,839
Speaker 1: money will find a home. How much of it will

777
00:40:59,840 --> 00:41:02,600
Speaker 1: get directed to the initiatives that actually need to get done,

778
00:41:03,320 --> 00:41:06,279
Speaker 1: formates to be seen, But I applaud the sort of

779
00:41:06,320 --> 00:41:07,879
Speaker 1: effort and the fact that there are more people who

780
00:41:07,880 --> 00:41:10,840
Speaker 1: care about it. How about that for a non answer

781
00:41:13,160 --> 00:41:15,080
Speaker 1: the price of pr That's a good that's a good

782
00:41:15,080 --> 00:41:18,080
Speaker 1: catch phrase. I actually, um, I'll sort of bring this

783
00:41:18,080 --> 00:41:19,880
Speaker 1: back a little bit of something I've been thinking about.

784
00:41:20,360 --> 00:41:23,239
Speaker 1: You know, obviously there's a lot of interest in E S.

785
00:41:23,280 --> 00:41:26,640
Speaker 1: G investing in general, but I've been more interested in

786
00:41:26,640 --> 00:41:28,680
Speaker 1: the S than the E and the G. And as

787
00:41:28,680 --> 00:41:31,719
Speaker 1: it relates to small companies. Something I've been doing some

788
00:41:31,760 --> 00:41:35,480
Speaker 1: work on and speaking to some academics about, is, you know,

789
00:41:35,680 --> 00:41:38,960
Speaker 1: can we link this idea that if you treat the

790
00:41:39,040 --> 00:41:42,439
Speaker 1: employees who work for you well, that your company will

791
00:41:42,480 --> 00:41:46,239
Speaker 1: outperform your competitors that don't. Now, the question for all

792
00:41:46,280 --> 00:41:48,600
Speaker 1: of us is how do you measure whether employees are

793
00:41:48,600 --> 00:41:51,000
Speaker 1: treated well or not? And can you go back long

794
00:41:51,080 --> 00:41:53,399
Speaker 1: enough to prove that out? But ideally, if you could

795
00:41:53,520 --> 00:41:56,120
Speaker 1: prove that in a rigorous way. There's some kind of

796
00:41:56,160 --> 00:41:58,560
Speaker 1: weakly ways of doing that now, but if you could

797
00:41:58,560 --> 00:42:01,000
Speaker 1: prove that in a in a rigor this way, you know,

798
00:42:01,000 --> 00:42:04,000
Speaker 1: maybe it would lower the cost of capital for these

799
00:42:04,040 --> 00:42:06,560
Speaker 1: companies that are doing good things for their employees or

800
00:42:06,600 --> 00:42:09,120
Speaker 1: something like that. It's sort of the same idea in bonds,

801
00:42:09,120 --> 00:42:11,960
Speaker 1: except on equities. I don't know, you know, it's it's

802
00:42:12,000 --> 00:42:14,560
Speaker 1: a tough one, and actually, if you ever have any

803
00:42:14,600 --> 00:42:18,399
Speaker 1: ideas around how one could measure that using publicly available data,

804
00:42:18,480 --> 00:42:20,839
Speaker 1: give me a call. Greg, Greg. All I'll say is,

805
00:42:21,000 --> 00:42:24,399
Speaker 1: as long as Bloomberg keeps providing free potato chips, I'm

806
00:42:24,400 --> 00:42:28,719
Speaker 1: a happy loyal employee for for the duration. Mike, for

807
00:42:28,760 --> 00:42:31,239
Speaker 1: the record, are they sending you shipments of them at home?

808
00:42:32,920 --> 00:42:36,279
Speaker 1: I can't. I can't discuss that. I show up to

809
00:42:36,320 --> 00:42:38,200
Speaker 1: the office every now and then and fill a backpack

810
00:42:38,239 --> 00:42:42,280
Speaker 1: and then then head back. Hey uh, Greg and Lisa,

811
00:42:42,520 --> 00:42:44,279
Speaker 1: thank you so much for your time. One of the

812
00:42:44,520 --> 00:42:47,400
Speaker 1: more fascinating conversations I've I've had in a while. Granted

813
00:42:47,400 --> 00:42:50,040
Speaker 1: the rest have been with my my teenage daughters, so

814
00:42:50,680 --> 00:42:52,560
Speaker 1: but I really appreciate your time. Hopefully we can have

815
00:42:52,600 --> 00:42:55,040
Speaker 1: you both back on the show sometimes. Oh it's been

816
00:42:55,080 --> 00:42:57,400
Speaker 1: a great time for me. Thank you. I enjoyed this

817
00:42:57,520 --> 00:42:59,920
Speaker 1: very much. Thank you. Thank you both, have one of

818
00:43:00,000 --> 00:43:09,839
Speaker 1: apter do what goes up. We'll be back next week.

819
00:43:10,040 --> 00:43:12,360
Speaker 1: Until then, you can find us on the Bloomberg Terminal,

820
00:43:12,440 --> 00:43:16,120
Speaker 1: website and app where wherever you get your podcasts. We'd

821
00:43:16,160 --> 00:43:17,680
Speaker 1: love it if you took the time to rate and

822
00:43:17,760 --> 00:43:20,640
Speaker 1: review the show on Apple podcasts so more listeners can

823
00:43:20,680 --> 00:43:24,000
Speaker 1: find us, and you can find us on Twitter, follow

824
00:43:24,080 --> 00:43:28,360
Speaker 1: me at Reaganonymous. Lisa brama Witz is at Lisa brama

825
00:43:28,400 --> 00:43:33,240
Speaker 1: Witz one. You can also follow Bloomberg Podcasts at at podcasts.

826
00:43:34,040 --> 00:43:36,160
Speaker 1: Thank you to Charlie Pellette of Bloomberg Radio and the

827
00:43:36,239 --> 00:43:38,960
Speaker 1: voice of the New York City Subway System. What Goes

828
00:43:39,040 --> 00:43:41,800
Speaker 1: Up is produced by Laura Carlson. The head of Bloomberg

829
00:43:41,800 --> 00:43:45,600
Speaker 1: podcast is Francesco Levy. Thanks for listening, See you next time.